CN116716864B - Seabed static sounding system and method for shallow stratum multiparameter survey - Google Patents
Seabed static sounding system and method for shallow stratum multiparameter survey Download PDFInfo
- Publication number
- CN116716864B CN116716864B CN202310995803.4A CN202310995803A CN116716864B CN 116716864 B CN116716864 B CN 116716864B CN 202310995803 A CN202310995803 A CN 202310995803A CN 116716864 B CN116716864 B CN 116716864B
- Authority
- CN
- China
- Prior art keywords
- parameter
- model
- survey
- seabed
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000003068 static effect Effects 0.000 title claims abstract description 63
- 238000000034 method Methods 0.000 title claims abstract description 49
- 239000000523 sample Substances 0.000 claims abstract description 57
- 238000005259 measurement Methods 0.000 claims abstract description 29
- 239000002689 soil Substances 0.000 claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 22
- 238000012545 processing Methods 0.000 claims abstract description 11
- 230000015572 biosynthetic process Effects 0.000 claims description 32
- 238000005755 formation reaction Methods 0.000 claims description 32
- 230000035699 permeability Effects 0.000 claims description 30
- 239000011148 porous material Substances 0.000 claims description 25
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 23
- 238000011065 in-situ storage Methods 0.000 claims description 20
- 238000013473 artificial intelligence Methods 0.000 claims description 13
- 230000006870 function Effects 0.000 claims description 12
- 238000004458 analytical method Methods 0.000 claims description 10
- 230000005251 gamma ray Effects 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 9
- 238000003860 storage Methods 0.000 claims description 9
- 239000004215 Carbon black (E152) Substances 0.000 claims description 7
- 229930195733 hydrocarbon Natural products 0.000 claims description 7
- 230000002441 reversible effect Effects 0.000 claims description 5
- 239000013535 sea water Substances 0.000 claims description 5
- 150000002430 hydrocarbons Chemical class 0.000 claims description 4
- 125000001183 hydrocarbyl group Chemical group 0.000 claims description 3
- 238000011835 investigation Methods 0.000 abstract description 4
- 238000005457 optimization Methods 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 description 11
- 238000005516 engineering process Methods 0.000 description 9
- 239000011435 rock Substances 0.000 description 9
- 230000008569 process Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 238000005553 drilling Methods 0.000 description 5
- 230000000704 physical effect Effects 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 238000012549 training Methods 0.000 description 4
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 3
- 229910052799 carbon Inorganic materials 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 239000007789 gas Substances 0.000 description 3
- 230000035515 penetration Effects 0.000 description 3
- 230000002285 radioactive effect Effects 0.000 description 3
- 230000009919 sequestration Effects 0.000 description 3
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 229910052739 hydrogen Inorganic materials 0.000 description 2
- 239000001257 hydrogen Substances 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001739 density measurement Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 238000009533 lab test Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000003904 radioactive pollution Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
- E02D1/00—Investigation of foundation soil in situ
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
The invention discloses a seabed static sounding system and a seabed static sounding method for shallow stratum multiparameter survey, wherein the system comprises the following components: a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe; the parameter survey module is used for lowering the multi-parameter sensor to the seabed of the target position through a propeller, filling the multifunctional probe into different stratum of the seabed, and collecting actual measurement data of a plurality of parameters of different stratum; the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result. According to the invention, a static sounding mode is adopted, a probe provided with a controllable neutron source, resistivity and CPT is directly poured into the seabed, so that the investigation and collection of shallow stratum parameters are realized, and meanwhile, a physical model and an optimization algorithm are combined, so that the investigation precision is improved.
Description
Technical Field
The invention relates to the technical field of marine geological survey, in particular to a seabed static sounding system and method for shallow stratum multiparameter survey.
Background
In the prior art, logging technology is widely applied and developed in petroleum exploration. Conventional logging techniques include resistivity logging, sonic logging, gamma ray logging, etc., which provide critical geological and reservoir information for oil exploration and development by measuring physical properties of subsurface rock and fluids.
However, the existing logging technology is mainly suitable for deep buried (the buried depth is more than 1000 meters) oil reservoirs, and has certain limitations for detecting shallow strata, particularly new energy shallow strata such as offshore wind power, marine carbon sequestration and the like in marine environments. The main limitations are the following: first, conventional logging techniques require the placement of a logging tool into the subterranean borehole through a drilling operation, but drilling operations may present difficulties in shallow formations such as formation tendencies, borehole collapse, etc. Secondly, due to the soft nature of the shallow stratum and the expanded diameter of the well, the traditional well logging method cannot obtain accurate stratum data, and the accuracy of stratum assessment and the feasibility of development are restricted. Third, conventional well logging methods use radioactive sources for measurements, with the risk of radioactive contamination and safety hazards. This is particularly sensitive and important in marine environments. In addition, conventional well logging methods are independent of other in situ testing operations, increase offshore operation time, and can lead to data inconsistencies, which can present challenges to overall exploration efficiency.
Accordingly, improvements and enhancements are needed in the art. The prior art also needs to explore new solutions including but not limited to developing a filling detection technology, pushing a logging technology without a radioactive source, developing a logging tool suitable for a shallow stratum, fusing the logging technology with other in-situ test operations and the like so as to meet the requirements of detecting the shallow stratum of new energy sources, and providing powerful support and guarantee for the development of the fields of offshore wind power, marine carbon sequestration and the like.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a seabed static sounding system and method for multi-parameter survey of shallow stratum aiming at the defects of the prior art, and aims to solve the problems that the well logging technology in the prior art is mainly suitable for deep buried (the buried depth is more than 1000 meters) oil reservoirs, and the conventional well logging technology has certain limitation on the detection of shallow stratum, particularly the detection of new energy shallow stratum such as offshore wind power and ocean carbon sequestration in the marine environment.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides a seabed static sounding system for shallow formation multiparameter surveys, wherein the system comprises:
a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe;
the parameter survey module is used for determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability;
the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result.
In one implementation, the survey equipment module includes the multi-function probe, the multi-parameter sensor, a pusher, a signal and data transmission cable, and a data recording system.
In one implementation, the multiparameter sensor has a controllable neutron source, resistivity and CPT measurement sensor mounted thereon.
In one implementation, the controllable neutron source includes one neutron emitter, a number of neutron receivers, and a number of gamma receivers.
In a second aspect, embodiments of the present invention further provide a method for seabed static sounding of a seabed static sounding system for shallow formation multiparameter survey, wherein the method comprises:
assembling a multifunctional survey apparatus, wherein a multi-parameter sensor of the multifunctional survey apparatus is mounted on a multifunctional probe;
determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, surveying and collecting actual measurement data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability;
and comparing the predicted parameter data in the geotechnical physical model with the measured data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the geotechnical physical model according to the comparison result.
In one implementation, before the assembling of the multifunctional survey apparatus, the method comprises:
acquiring initial data of the parameters, and constructing a plurality of rock-soil physical models based on artificial intelligence based on the initial data, wherein the rock-soil physical models comprise a porosity model, a saturation model and a permeability model;
the porosity model includes: azithrombi model:
，
wherein ，mAnda 0 is a physical parameter that is a function of the physical parameters,a e is an empirically-adjustable parameter that is used to adjust the parameters,R 0 is the in situ measured formation full water saturation resistivity,R w is the formation pure water resistivity, Φ is the porosity, and
gamma ray density porosity model:
，
wherein ,ρma and ρf Is a physical parameter that is a function of the physical parameters,a e is an empirically adjustable parameter ρ b Is the in situ measured density ρ ma Is the skeleton density in the rock-soil model, ρ w Is the sea water density;
the saturation model includes: gamma ray density saturation model:
，
wherein ,S w is the saturation, ρ ma ，ρ w and ρhc Is a physical parameter, a e Is an empirically adjustable parameter ρ hc Is the hydrocarbon density and resistivity saturation model:
，
wherein n is a physical parameter,a e is an empirically adjustable parameter, R t Is the in situ measured resistivity of the hydrocarbon-bearing formation;
the permeability model includes:
，
wherein ,K 0 anda 0 is a physical parameter, a e Is an empirically-adjustable parameter that is used to adjust the parameters,K 0 as a static measured permeability of the reference point,Φ 0 is the porosity of the reference point and,K s is the calculated dynamic continuous in situ permeability.
In one implementation, after the survey and acquisition of measured data of several parameters of different formations, the multifunctional probe is removed from the seabed by reverse propulsion.
In one implementation, after calibrating the parameter data of the geotechnical physical model according to the comparison result, a final survey parameter and an analysis report are output.
In a third aspect, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a seabed static sounding program stored in the memory and capable of running on the processor for shallow layer multi-parameter surveying, and when the processor executes the seabed static sounding program for shallow layer multi-parameter surveying, the step of the seabed static sounding method according to any of the above schemes is implemented.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores a seabed static sounding program for shallow stratum multiparameter survey, where the seabed static sounding program for shallow stratum multiparameter survey implements the steps of the seabed static sounding method according to any of the above schemes when the seabed static sounding program is executed by a processor.
The beneficial effects are that: compared with the prior art, the invention provides a seabed static sounding system for shallow stratum multiparameter survey, which comprises the following components: and the survey equipment module is used for assembling the multifunctional survey equipment, wherein the multi-parameter sensor of the multifunctional survey equipment is arranged on the multifunctional probe, and the multi-parameter sensor of the multifunctional probe is connected with the probe head. And the parameter surveying module is used for determining a target surveying position, lowering the multi-parameter sensor to the seabed of the target surveying position through a propeller, pouring the multifunctional probe into different stratum of the seabed, surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability. And finally, the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligence algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result. The surveying equipment adopts a static sounding mode, the multifunctional probe is directly poured into the seabed, the limitation of the traditional logging technology in the shallow surface stratum can be overcome, the surveying and the acquisition of shallow stratum parameters are realized, the multifunctional probe in the multifunctional surveying equipment can also acquire various stratum parameters at one time, and the data acquisition efficiency is further improved. Meanwhile, the invention also constructs a rock-soil physical model algorithm based on artificial intelligence, and can improve the accuracy of parameters in the constructed rock physical model by continuously calibrating the rock physical model.
Drawings
FIG. 1 is a functional schematic of a seabed static sounding system for shallow stratum multiparameter survey according to an embodiment of the present invention.
Fig. 2 is an assembly schematic diagram of a multi-parameter sensor and a multi-functional probe according to an embodiment of the present invention.
FIG. 3 is a flow chart of an embodiment of a method for sea bed cone penetration for shallow formation multiparameter surveys provided by an embodiment of the present invention.
Fig. 4 is a schematic diagram of a process for acquiring parameter data according to an embodiment of the present invention.
Fig. 5 is a flowchart of a calibration rock physical model provided in an embodiment of the present invention.
FIG. 6 is a flowchart of intelligent determination of static data measurement point positions through man-machine interaction according to an embodiment of the present invention
Fig. 7 is a schematic block diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and more specific, the present invention will be described in further detail below with reference to the accompanying drawings and examples.
It will be appreciated by persons skilled in the art that the specific embodiments described herein are for purposes of illustration only and are not intended to be limiting. As used herein, the singular forms "a," "an," "the" and "the" are intended to include the plural forms as well, and the word "comprising" when used in the specification of the present invention means that there are one or more of the stated features, integers, steps, operations, elements, and/or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
The present embodiment provides a seabed static sounding system for shallow stratum multiparameter survey, specifically, the seabed static sounding system of the present embodiment includes: a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe; the parameter survey module is used for determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability; the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result. The survey equipment of this embodiment adopts the mode of static sounding, directly fills the seabed with multi-functional probe, can overcome traditional logging technique in shallow surface stratum's limitation, realizes surveying and gathering shallow stratum parameter, and multi-parameter sensor in the multi-functional survey equipment can also once gather multiple stratum parameter, has further improved data acquisition's efficiency. Meanwhile, an artificial intelligence-based rock-soil physical model algorithm is also constructed in the embodiment, and the accuracy of parameters in the constructed rock physical model can be improved by continuously calibrating the rock physical model.
For example, the in-situ testing technique overcomes the problems of the shallow stratum of softness and borehole collapse because the in-situ testing technique is not required to perform drilling operations, as the parameter data in the shallow stratum is surveyed by directly pouring the multifunctional probe into the seabed in this embodiment. Meanwhile, when the probe is filled into the shallow stratum, as the multi-parameter sensor is connected with the multifunctional probe and is provided with the controllable neutron source, the resistivity and the CPT measuring sensor, the surveying equipment can acquire various physical characteristics of different stratum for a time, such as: the porosity, density, saturation, permeability and the like, so that the data of various parameters in the shallow stratum can be obtained once through improving the survey system, the data difference caused by the fact that the probe is required to be poured into the underground for collecting the data for many times can be avoided, and the accuracy and reliability of stratum parameter estimation are improved.
Exemplary apparatus
As shown in fig. 1, the present invention provides a seabed static sounding system for shallow formation multiparameter surveys, comprising: a survey equipment module 10, a parametric survey module 20, a data processing module 30.
In particular, the survey apparatus module 10 is used for assembling a multifunctional survey apparatus, wherein the multi-parameter sensors of the multifunctional survey apparatus are mounted on a multifunctional probe.
The parameter survey module 20 is configured to determine a target survey location, lower the multi-parameter sensor to a seabed of the target survey location by a pusher, pour the multi-function probe into different strata of the seabed, and survey and collect measured data of several parameters of the different strata, wherein the parameters include cone tip resistance, sidewall resistance, pore water pore pressure, porosity, density, resistivity, and permeability.
The data processing module 30 is configured to compare, in real time, the predicted parameter data with the measured data in the geotechnical physical model through an artificial intelligence algorithm, and calibrate the parameter data of the geotechnical physical model according to the comparison result.
In one implementation, the survey equipment module 10 includes the multi-function probe, the multi-parameter sensor, a pusher, a signal and data transmission cable, and a data recording system.
In practice, in order to conduct a shallow multi-parameter survey, the present embodiment requires preferential assembly of a multi-function survey apparatus, wherein the multi-function survey apparatus includes a multi-function probe, multi-parameter sensors, a pusher, signal and data transmission cables, and a data recording system.
Specifically, the data acquisition system consists of a multi-parameter sensor and a multifunctional probe, wherein the multi-parameter sensor is arranged on the multifunctional probe and is used for acquiring stratum parameter data. The propeller is used for controlling the movement of the data acquisition system on the sea floor. A data recording system is positioned on the deck for recording and analyzing formation parameter data. And two ends of the signal and data transmission cable are respectively connected with the data acquisition system and the data recording system, and are used for transmitting stratum parameter data acquired by the acquisition system to the data recording system.
In practice, after the engineer has determined the target survey location based on the survey requirements, the data acquisition system is lowered on deck to the seabed at the target survey location by means of a propeller. Then, the propeller pushes the probe to penetrate the stratum downwards to drive the multifunctional probe on the data acquisition system to be filled into different strata, and the multi-parameter sensor of the data acquisition system measures the physical characteristics of different strata, including resistivity, stratum hydrogen index, secondary gamma intensity generated by the controllable neutron source, cone tip resistance, side wall resistance, pore water pore pressure and the like, and acquires the stratum parameter data simultaneously, wherein the stratum parameter data are transmitted to the data recording system on the deck in real time through signals and data transmission cables in the process. Finally, the various parameter data collected is processed and analyzed on a data recording system on the deck.
Preferably, the embodiment adopts the technology of directly filling the multifunctional probe into the seabed, a logging tool is not required to be put into an underground borehole through a series of drilling operations, the problems of formation softness, borehole collapse and the like possibly faced by the drilling operations in shallow stratum are effectively avoided, and the method is more suitable for the investigation of shallow stratum. As shown in fig. 2, the data acquisition system of the present embodiment is adapted to survey shallow subsurface formations.
Further, as shown in FIG. 2, the multiparameter sensor has mounted thereon a controllable neutron source, resistivity and CPT measurement sensor. In addition, the resistivity in the present embodiment includes four different electrodes, namely, electrode a, electrode B, electrode M and electrode N. When measuring low resistance, by dividing four electrodes into two groups of different leads, such as electrode A and electrode B, electrode M and electrode N, errors introduced by lead resistance can be effectively eliminated, and measurement accuracy is further improved.
This embodiment enables the survey apparatus to acquire multiple physical properties of different formations one time by installing controllable neutron sources, resistivity and CPT measurement sensors on a multiparameter sensor, including: the secondary gamma intensity, cone tip resistance, side wall resistance and pore water pore pressure generated by the controllable neutron source and parameters such as porosity, density, resistivity, pore water pressure and friction force of different stratum are controlled, so that acquired data have higher consistency, data difference caused by different operations is reduced, and accuracy and reliability of stratum parameter estimation are improved. Finally, the multiple parameters collected in this embodiment are used to provide critical data support for subsequent calculation of important parameters such as porosity, saturation and permeability.
Further, the controllable neutron source in this embodiment further includes a neutron emitter, a plurality of neutron receivers, and a plurality of gamma receivers. According to the embodiment, a controllable neutron source is adopted to replace an active radioactivity measurement mode, so that radioactive pollution and radiation risks of operators are reduced, the safety of in-situ operation is improved, environmental pollution and radiation risks possibly existing in a traditional well logging method can be avoided, and the safety coefficient of survey equipment is improved.
Exemplary method
Based on the above embodiment, the embodiment of the present invention further provides a seabed static sounding method for shallow stratum multiparameter survey, and the seabed static sounding method for shallow stratum multiparameter survey of the present embodiment may be applied to the seabed static sounding system of the above embodiment. Specifically, the steps of the seabed static sounding method in the embodiment are the same as the working principle of each module in the method embodiment. As shown in fig. 3, the static sounding method for the seabed of the present embodiment comprises the following steps:
step S100, assembling the multifunctional surveying device, wherein a multi-parameter sensor of the multifunctional surveying device is mounted on a multifunctional probe.
The process of assembling the multifunctional survey apparatus of the present embodiment is performed on deck. The multifunctional survey apparatus includes a multifunctional probe, a multi-parameter sensor, a pusher, a signal and data transmission cable, and a data recording system. That is, the data acquisition system is composed of a multi-parameter sensor mounted on the multi-function probe for acquiring formation parameter data, together with the multi-function probe. The propeller is used for controlling the movement of the data acquisition system on the sea floor. A data recording system is positioned on the deck for recording and analyzing formation parameter data. And two ends of the signal and data transmission cable are respectively connected with the data acquisition system and the data recording system, and are used for transmitting stratum parameter data acquired by the acquisition system to the data recording system.
This embodiment further includes, prior to assembling the multifunctional survey apparatus on the deck: checking well position coordinates and filling depth, namely: the site engineer first needs to preset the target site, well location coordinates and the filling depth of the offshore operation according to the construction design unit, and checks the well location coordinates and the filling depth before the survey vessel or platform is in place. Then, the wellhead geology is evaluated, namely: the field engineer should pre-judge the geological condition of the wellhead and the filling area, and should take corresponding measures for the specific stratum, for example, the hard seabed exceeding the capacity of the propeller, and the field engineer should adjust the well position. Finally, a geotechnical physical model is constructed, namely: based on the existing laboratory tests and geological data, a geotechnical physical model suitable for the investigation region is established, and corresponding physical parameters are determined.
In one implementation, the process of constructing the geotechnical physical model includes the steps of:
step S001, obtaining initial data of the parameters, and constructing a plurality of geotechnical physical models based on artificial intelligence based on the initial data, wherein the geotechnical physical models comprise a porosity model, a saturation model and a permeability model.
The embodiment obtains accurate and reliable original data such as porosity, saturation, permeability and the like on the basis of comprehensively analyzing shallow stratum geological interpretation and China offshore geophysical data, and builds a porosity model, a saturation model and a permeability model based on the original data. When the survey requirements are different and the survey areas are different, the acquired parameters are different, and the corresponding petrophysical models are also different, so that the physical parameters and the empirically adjustable parameters are arranged in each petrophysical model.
Specifically, the porosity model includes: azithrombi model:
，
wherein ，mAnda 0 is a physical parameter that is a function of the physical parameters,a e is an empirically-adjustable parameter that is used to adjust the parameters,R 0 is the in situ measured formation full water saturation resistivity,R w is the resistivity of the stratum pure water, and phi is the porosity; and
gamma ray density porosity model:
，
wherein ,ρma and ρf Is a physical parameter that is a function of the physical parameters,a e is an empirically adjustable parameter ρ b Is the in situ measured density ρ ma Is the skeleton density in the rock-soil model, ρ w Is the sea water density.
Specifically, the saturation model includes:
gamma ray density saturation model (Gamma-Ray Density Saturation): using gamma rays and density measurements, in combination with a porosity model, calculate saturation (Sw),
，
wherein ,ρma ，ρ w and ρhc Is a physical parameter, a e Is an empirically adjustable parameter. Since in the saturation model, the formation is assumed to contain not only sea water, but also oil and gas, ρ hc Representing hydrocarbon density, typically gas density. In particular applications, specific density values should be evaluated based on actual geological and gas property data.
Resistivity saturation model (Resistivity Saturation): calculating saturation by combining the resistivity measurement result with a porosity model and a resistivity-saturation relation modelS w ）：
，
Wherein n is a physical parameter,a e is an empirically adjustable parameter, R t Is the source of the stratum containing oil and gasThe bit measured resistivity.
Specifically, the permeability model includes:
permeability-porosity relationship model: based on experimental measurements and theoretical derivations, the relationship between permeability and porosity is described:
，
wherein ,K 0 and a0 Is a physical parameter that is a function of the physical parameters,a e is an empirically-adjustable parameter that is used to adjust the parameters,K 0 as a static measured permeability of the reference point,Φ 0 is the porosity of the reference point and,K s is the calculated dynamic continuous in situ permeability.
Step 200, determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting actual measurement data of a plurality of parameters of the different stratum.
Specifically, the target survey position of the present embodiment is a target site, well position coordinates, and a filling depth of an offshore operation that are preset by a construction design unit. After the target survey position is determined, the data acquisition system (comprising the multi-parameter sensor and the multi-function probe) of the assembled multi-function survey apparatus is lowered to the seabed of the target survey position, and physical properties of different strata are surveyed and acquired in real time as the multi-function probe is poured into the different strata.
The process of lowering the apparatus in this embodiment is referred to as a seabed preparation process, and includes, but is not limited to: the propeller is lowered, namely the propeller is slowly lowered to the seabed and is controlled by ropes or steel cables, so that the equipment is ensured to be lowered vertically; and the propeller is seated, and the position coordinates of the propeller are checked before the propeller is seated, if there is a deviation, the embodiment also properly adjusts the position of the propeller, and ensures the stability and reliability of the propeller, so that the final position of the base is the target survey position.
After the seabed is prepared, the multifunctional survey apparatus begins to survey parameter data for different formations. Further, as shown in fig. 4, the process of collecting parameter data in this embodiment is divided into continuous dynamic measurement and fixed point static measurement. The continuous dynamic measurement means that lithology physical property and mechanical parameter data are continuously recorded in the pushing process, namely, when the pusher pushes the probe to penetrate the stratum downwards, physical characteristics of different strata are measured by equipment, and the physical characteristics comprise parameter data such as resistivity, stratum hydrogen index, secondary gamma intensity generated by a controllable neutron source, cone tip resistance, side wall resistance, pore water pore pressure and the like. The fixed-point static measurement means that when the propeller stops propelling, equipment measures stratum physical properties and mechanical parameters, static data are used for calibrating dynamic data in a geotechnical physical model, and selection of static test points is determined by a field engineer according to recommendation of an artificial intelligent algorithm and actual field conditions.
Finally, the embodiment transmits the collected stratum parameter data to a data recording system for analysis through a signal and data transmission cable.
In one implementation, after the step S200, the method includes:
step S201, the multifunctional probe is taken out of the seabed in a reverse propulsion mode.
In a specific implementation, after the multifunctional survey apparatus of this embodiment completes data acquisition, the multifunctional probe may be taken out from the seabed by way of reverse propulsion, for example: the reverse pushing function of the pusher is used, or alternatively, the multifunctional probe is removed from the seabed or shallow seabed soil by other methods, and the embodiment is not particularly limited.
And step S300, comparing predicted parameter data in the geotechnical physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the geotechnical physical model according to a comparison result.
In this embodiment, the formation parameter data is calibrated by combining an artificial intelligence algorithm with a geotechnical physical model. As shown in fig. 5, the process of calibrating a geotechnical physical model according to the present embodiment includes: first, based on the analysis requirements, a corresponding geotechnical physical model is selected and relevant formation parameters are determined. Such as: when the analysis requirement is in terms of resistanceWhen the measured value of the porosity is taken as an input characteristic and the porosity is taken as a target variable, namely the input value is resistivity and the predicted value is porosity, an Azithrone model and an empirically adjustable parameter are selected at the momenta e A query range may be set, such as 0.5, 1.5]。
Further, the collected parameter data is classified based on the selected geotechnical physical model. Specifically, the artificial intelligence algorithm sets two fixed calibration depths when the fixed point static measurement data are set, and the two fixed calibration depths are respectively located after the equipment is completely cemented for 2-3 meters and at a preset target depth. The floating calibration point adopts a man-machine combination mode, and the artificial intelligence calculates the depth and the field engineer decides whether to adopt. And when the probe reaches the calibration depth, the probe stops pushing, and the change conditions of stratum physical parameters and mechanical parameters at the same depth are measured in a static state. The measured fixed point record data set is then separated into a training set and a test set, the training set being model trained using artificial intelligence, such as support vector machine algorithms. In support vector machines, it is necessary to select the appropriate kernel functions (e.g., linear kernel, polynomial kernel, radial basis kernel, etc.) and associated hyper-parameters, such as regularization parameters and penalty terms. In this embodiment, 70% of data is generally used as the training set, 30% of data is used as the test set, and the parameters are adjusted empiricallya e Setting the number of cycles of data training, e.g. in empirically adjustable parametersa e Query scope [0.5, 1.5 ]]The cycle was set up 100 times with a start value of 0.5, 0.01 increase each time.
In each cycle, the artificial intelligence algorithm will correct the physical parameters and determine the empirically tunable parameters by comparing the consistency of the geotechnical physical model prediction parameter data and the measured parameter data in real time. As shown in fig. 6, in this embodiment, the human-computer interaction intelligently determines the positions of the static data measurement points until the threshold value is smaller than the preset value, and then no new static test points are recommended, that is, calibration dynamic data in the geotechnical physical model is determined according to the measured data of the current static test points; when the real-time prediction and actual test results are larger than a threshold value, for example +/-10%, the algorithm control equipment outputs a reminding prompt of 'equipment checking', and if the field engineer equipment works normally, fixed-point sampling points are increased, and then the model is retrained.
At the same time, the present embodiment will control the speed of propulsion and penetration according to the test requirements to ensure accurate data is obtained, for example, the speed of propulsion of the survey apparatus may be set to between a few tens of centimeters per minute and a hundred centimeters per minute.
Finally, the calibrated petrophysical model will be used to calculate relevant formation parameters such as porosity, saturation, lithology, formation thickness, etc., and for the next shallow formation survey project. For example, when the calibrated and verified model is applied to actual field data acquisition, the resistivity obtained by continuous measurement can be used for obtaining calculated porosity through an Azithro porosity model, and then the calculated porosity is compared with actual neutron porosity obtained by a controllable neutron source to obtain the bound water content of the argillaceous rock, and the accuracy of the actual neutron porosity is improved after the neutron porosity deducts the bound water content.
In one implementation, after the step S300, the method includes:
step S400, outputting final survey parameters and analysis reports.
In particular, the present embodiment also outputs an analysis report for calibrating the geotechnical physical model to assist the later data applicator in understanding the behavior and improvement of the model more deeply. For example, when outputting parametric survey analysis reports about a wind farm, these conclusions and suggestions may be used for the development of a later site, for operation and site monitoring of the wind farm, etc.
Preferably, the analysis report output in this embodiment may be a geological evaluation report, i.e. a result of using logging and static sounding data, for geological evaluation and geological model construction to better understand the subsurface geological conditions. The engineering design report can also be used for making engineering design and construction scheme according to stratum parameters and characteristics provided by logging and static sounding data. The system may also be a digital report (including an electronic version petrophysical model and a model analysis report), including a program of the petrophysical model and a description of the petrophysical model, and also including necessary formulas and formula parameter selection, which are not particularly limited in this embodiment.
In summary, the present embodiment provides a seabed static sounding system for shallow stratum multiparameter survey, and when the system is implemented, the system includes: a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe; the parameter survey module is used for determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability; the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result. The survey equipment of this embodiment adopts the mode of static sounding, directly fills the seabed with multi-functional probe, can overcome traditional logging technique in shallow surface stratum's limitation, realizes surveying and gathering shallow stratum parameter, and multi-parameter sensor in the multi-functional survey equipment can also once gather multiple stratum parameter, has further improved data acquisition's efficiency. Meanwhile, an artificial intelligence-based rock-soil physical model algorithm is also constructed in the embodiment, and the accuracy of parameters in the constructed rock physical model can be improved by continuously calibrating the rock physical model.
Based on the above embodiment, the present invention also provides a terminal device, and a schematic block diagram of the terminal device may be shown in fig. 7. The terminal device may include one or more processors 100 (only one shown in fig. 7), a memory 101, and a computer program 102 stored in the memory 101 and executable on the one or more processors 100, such as a seabed static sounding program for shallow layer multiparameter surveys. The one or more processors 100, when executing the computer program 102, may implement various steps in embodiments of a seabed static sounding method for shallow multi-parameter surveys of formations. Alternatively, the one or more processors 100, when executing the computer program 102, may perform the functions of the various modules/units of the embodiments of the seabed static cone penetration apparatus, without limitation.
In one embodiment, the processor 100 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In one embodiment, the memory 101 may be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory 101 may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the electronic device. Further, the memory 101 may also include both an internal storage unit and an external storage device of the electronic device. The memory 101 is used to store computer programs and other programs and data required by the terminal device. The memory 101 may also be used to temporarily store data that has been output or is to be output.
It will be appreciated by persons skilled in the art that the functional block diagram shown in fig. 7 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal device to which the present inventive arrangements are applied, and that a particular terminal device may include more or fewer components than shown, or may combine some of the components, or may have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, that when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, operational database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operation data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the present invention discloses a system and method for sea bed static sounding for shallow stratum multiparameter surveys, the system comprising: a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe; the parameter survey module is used for determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability; the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result. According to the invention, a static sounding mode is adopted, the probe is directly poured into the seabed to realize the survey and collection of shallow stratum parameters, and meanwhile, a physical model and an optimization algorithm are combined, so that the survey precision is improved.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A seabed static sounding system for shallow stratum multiparameter survey, the system comprising:
a survey equipment module for assembling a multifunctional survey equipment, wherein a multi-parameter sensor of the multifunctional survey equipment is mounted on a multifunctional probe;
the parameter survey module is used for determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, and surveying and collecting measured data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability;
the data processing module is used for comparing the predicted parameter data in the rock-soil physical model with the actual measurement data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to the comparison result, wherein the rock-soil physical model comprises a porosity model, a saturation model and a permeability model;
the porosity model includes: azithrombi model:
，
wherein ，mAnda 0 is a physical parameter that is a function of the physical parameters,a e is an empirically-adjustable parameter that is used to adjust the parameters,R 0 is the in situ measured formation full water saturation resistivity,R w is the formation pure water resistivity, Φ is the porosity, and
gamma ray density porosity model:
，
wherein ,ρma and ρf Is a physical parameter that is a function of the physical parameters,a e is an empirically adjustable parameter ρ b Is the in situ measured density ρ ma Is the skeleton density in the rock-soil model, ρ w Is the sea water density;
the saturation model includes: gamma ray density saturation model:
，
wherein ,S w is the saturation, ρ ma 、ρ w and ρhc Is a physical parameter, a e Is an empirically adjustable parameter ρ hc Is the hydrocarbon density and resistivity saturation model:
，
wherein n is a physical parameter,a e is an empirically-adjustable parameter that is used to adjust the parameters,R t is the in situ measured resistivity of the hydrocarbon-bearing formation;
the permeability model includes:
，
wherein ,K 0 anda 0 is a physical parameter, a e Is an empirically-adjustable parameter that is used to adjust the parameters,K 0 as a static measured permeability of the reference point,Φ 0 is the porosity of the reference point and,K s is the calculated dynamic continuous in situ permeability.
2. A seabed static sounding system for shallow-layer multiparameter surveying according to claim 1, wherein the survey equipment module comprises the multifunction probe, the multiparameter sensor, propeller, signal and data transmission cable and data recording system.
3. The system of claim 2, wherein the multiparameter sensor has a controllable neutron source, resistivity and CPT measurement sensor mounted thereon.
4. A seabed static sounding system for shallow stratum multiparameter surveying according to claim 3, wherein the controllable neutron source comprises one neutron emitter, a number of neutron receivers and a number of gamma receivers.
5. A method of seabed static sounding based on a seabed static sounding system for shallow stratum multiparameter surveying according to any of the preceding claims 1 to 4, wherein the method comprises:
assembling a multifunctional survey apparatus, wherein a multi-parameter sensor of the multifunctional survey apparatus is mounted on a multifunctional probe;
determining a target survey position, lowering the multi-parameter sensor to the seabed of the target survey position through a propeller, pouring the multifunctional probe into different stratum of the seabed, surveying and collecting actual measurement data of a plurality of parameters of different stratum, wherein the parameters comprise cone tip resistance, side wall resistance, pore water pore pressure, porosity, density, resistivity and permeability;
comparing predicted parameter data in the rock-soil physical model with the measured data in real time through an artificial intelligent algorithm, and calibrating the parameter data of the rock-soil physical model according to a comparison result;
before the multifunctional survey apparatus is assembled, comprising:
acquiring initial data of the parameters, and constructing a plurality of rock-soil physical models based on artificial intelligence based on the initial data, wherein the rock-soil physical models comprise a porosity model, a saturation model and a permeability model;
the porosity model includes: azithrombi model:
，
wherein ，mAnda 0 is a physical parameter that is a function of the physical parameters,a e is an empirically-adjustable parameter that is used to adjust the parameters,R 0 is the in situ measured formation full water saturation resistivity,R w is the formation pure water resistivity, Φ is the porosity, and
gamma ray density porosity model:
，
wherein ,ρma and ρf Is a physical parameter that is a function of the physical parameters,a e is an empirically adjustable parameter ρ b Is the in situ measured density ρ ma Is the skeleton density in the rock-soil model, ρ w Is the sea water density;
the saturation model includes: gamma ray density saturation model:
，
wherein ,S w is the saturation, ρ ma 、ρ w and ρhc Is a physical parameter, a e Is an empirically adjustable parameter ρ hc Is the hydrocarbon density and resistivity saturation model:
，
wherein n is a physical parameter,a e is an empirically-adjustable parameter that is used to adjust the parameters,R t is the in situ measured resistivity of the hydrocarbon-bearing formation;
the permeability model includes:
，
wherein ,K 0 anda 0 is a physical parameter, a e Is an empirically-adjustable parameter that is used to adjust the parameters,K 0 as a static measured permeability of the reference point,Φ 0 is the porosity of the reference point and,K s is the calculated dynamic continuous in situ permeability.
6. The method of claim 5, wherein after the survey and acquisition of measured data of several parameters of different formations, the multifunctional probe is removed from the seabed by reverse propulsion.
7. The method according to claim 5, wherein the final survey parameters and analysis report are output after the parameter data of the geotechnical physical model are calibrated according to the comparison result.
8. A terminal device comprising a memory, a processor and a seabed static sounding program for shallow multi-parameter surveying stored in the memory and operable on the processor, when executing the seabed static sounding program for shallow multi-parameter surveying, carrying out the steps of the seabed static sounding method as claimed in any of claims 5 to 7.
9. A computer readable storage medium, characterized in that it has stored thereon a seabed static sounding program for shallow multi-parameter surveying, which, when executed by a processor, implements the steps of the seabed static sounding method according to any of claims 5-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310995803.4A CN116716864B (en) | 2023-08-09 | 2023-08-09 | Seabed static sounding system and method for shallow stratum multiparameter survey |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310995803.4A CN116716864B (en) | 2023-08-09 | 2023-08-09 | Seabed static sounding system and method for shallow stratum multiparameter survey |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116716864A CN116716864A (en) | 2023-09-08 |
| CN116716864B true CN116716864B (en) | 2023-10-27 |
Family
ID=87864700
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310995803.4A Active CN116716864B (en) | 2023-08-09 | 2023-08-09 | Seabed static sounding system and method for shallow stratum multiparameter survey |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116716864B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106498919A (en) * | 2016-10-27 | 2017-03-15 | 东南大学 | A kind of sea bed formula static cone penetration equipment from dynamic(al) correction perpendicularity |
| CN107700458A (en) * | 2017-10-16 | 2018-02-16 | 东南大学 | Feeler inspection is flowed entirely with the pyriform base expanding and base expanding of Yu Haiyang ultra-soft soil in-situ test to pop one's head in |
| CN107747306A (en) * | 2017-11-07 | 2018-03-02 | 东南大学 | A kind of cross with Yu Haiyang ultra-soft soil in-situ test flows feeler inspection probe entirely |
| CN108106965A (en) * | 2017-12-25 | 2018-06-01 | 国家海洋局第二海洋研究所 | A kind of seabed sediment acoustics and physical parameter in-situ synchronization measuring device and method |
| EP3351974A1 (en) * | 2017-01-18 | 2018-07-25 | Qingdao Institute Of Marine Geology | Static cone penetration combined type geochemical microelectrode probe system |
| WO2022110986A1 (en) * | 2020-11-30 | 2022-06-02 | 浙江大学 | Subsea geotechnical in-situ multi-parameter detection system and method |
-
2023
- 2023-08-09 CN CN202310995803.4A patent/CN116716864B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106498919A (en) * | 2016-10-27 | 2017-03-15 | 东南大学 | A kind of sea bed formula static cone penetration equipment from dynamic(al) correction perpendicularity |
| EP3351974A1 (en) * | 2017-01-18 | 2018-07-25 | Qingdao Institute Of Marine Geology | Static cone penetration combined type geochemical microelectrode probe system |
| CN107700458A (en) * | 2017-10-16 | 2018-02-16 | 东南大学 | Feeler inspection is flowed entirely with the pyriform base expanding and base expanding of Yu Haiyang ultra-soft soil in-situ test to pop one's head in |
| CN107747306A (en) * | 2017-11-07 | 2018-03-02 | 东南大学 | A kind of cross with Yu Haiyang ultra-soft soil in-situ test flows feeler inspection probe entirely |
| CN108106965A (en) * | 2017-12-25 | 2018-06-01 | 国家海洋局第二海洋研究所 | A kind of seabed sediment acoustics and physical parameter in-situ synchronization measuring device and method |
| WO2022110986A1 (en) * | 2020-11-30 | 2022-06-02 | 浙江大学 | Subsea geotechnical in-situ multi-parameter detection system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116716864A (en) | 2023-09-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| RU2321064C2 (en) | Method for building a reversible three-dimensional hydrodynamic model of earth, calibrated in real time during drilling | |
| US10386531B2 (en) | Geological model analysis incorporating cross-well electromagnetic measurements | |
| US8244473B2 (en) | System and method for automated data analysis and parameter selection | |
| CN101240705B (en) | Nuclear tool | |
| US20140052376A1 (en) | Method for Cement Evaluation with Acoustic and Nuclear Density Logs | |
| BR112018072718B1 (en) | METHOD AND APPARATUS FOR ESTIMATING AN INVERTED PARAMETER OF A SUBSURFACE FORMATION | |
| EA007587B1 (en) | Directional electromagnetic wave resistivity apparatus and method | |
| BRPI1001536A2 (en) | Method for determining effective permeability of terrestrial formations | |
| CN103375166A (en) | Method for determining content of a plurality of mineral constituents in stratum | |
| US10495524B2 (en) | Apparatus and method for monitoring production wells | |
| CN103649781A (en) | Azimuthal brittleness logging systems and methods | |
| CN105629308A (en) | Phase control heterogeneous mechanical parameter crustal stress prediction method | |
| CN104153768A (en) | Granite reservoir stratum reservoir performance evaluation method | |
| Bonneville et al. | Time-lapse borehole gravity imaging of CO2 injection and withdrawal in a closed carbonate reef | |
| CN110244354A (en) | A kind of metal mine mining disturbance stress field quantifies dynamic playback method | |
| CN116716864B (en) | Seabed static sounding system and method for shallow stratum multiparameter survey | |
| CN105464650A (en) | Interpretation method for well logging during drilling | |
| Tran | Characterisation and modelling of naturally fractured reservoirs | |
| US9213117B2 (en) | Dip seismic attributes | |
| KR102519630B1 (en) | Method and apparatus for determination a working point on the seabed | |
| US11474272B2 (en) | Methods and systems for identifying and plugging subterranean conduits | |
| US9366777B2 (en) | Measurement of permeability in borehole in the presence of mudcake | |
| CN111123378B (en) | Method and device for determining gamma ray intensity critical value for dividing lithology type | |
| CN113240250B (en) | Accurate ocean topography system | |
| Dai et al. | Borehole tool for the comprehensive characterization of hydrate-bearing sediments |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |